LQDeployConfig/prod/models/glm_ocr/docker-compose.yml

services:
  glm-ocr-vllm-docker:
    image: vllm/vllm-openai:nightly
    container_name: glm-ocr-vllm
    runtime: nvidia
    restart: unless-stopped
    environment:
      - PYTHONUNBUFFERED=1
      - PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
      - PIP_TRUSTED_HOST=pypi.tuna.tsinghua.edu.cn
      - PYTHONPATH=/opt/pip-packages:/usr/local/lib/python3.12/dist-packages
    ports:
      - "25429:30000"
    volumes:
      - /data/app_workspace/models/GLM-OCR:/models/GLM-OCR:ro
      - /data/app_workspace/glm-ocr/logs-docker:/var/log/vllm
      - /data/app_workspace/glm-ocr/pip-packages:/opt/pip-packages:rw
      - /data/app_workspace/glm-ocr/pip-cache:/root/.cache/pip:rw
    entrypoint: ["/bin/bash", "-c"]
    command:
      - |
        # 关键修改：优先检查缓存，只在需要时安装
        echo "=== 检查 transformers 版本 ==="
        if python3 -c "import transformers; assert transformers.__version__ >= '5.3.0', f'需要 transformers>=5.3.0，当前版本 {transformers.__version__}'" 2>/dev/null; then
          echo "✅ 使用已安装的 transformers $(python3 -c 'import transformers; print(transformers.__version__)')"
        else
          echo "⚠️ 安装或更新 transformers>=5.3.0..."
          pip3 install "transformers>=5.3.0" \
            --target /opt/pip-packages \
            --root-user-action=ignore \
            -q 2>&1 | tail -5
        fi
        
        echo "=== 启动 vLLM ==="
        python3 -m vllm.entrypoints.openai.api_server \
          --model /models/GLM-OCR \
          --served-model-name GLM-OCR \
          --host 0.0.0.0 \
          --port 30000 \
          --api-key sk_prod_sXgHYxfVvZdw7O-cki6i7Cp2TbguOvbA_f4beb12a \
          --gpu-memory-utilization 0.60 \
          --max-model-len 4096 \
          --max-num-seqs 96 \
          --enable-prefix-caching \
          --trust-remote-code \
          --allowed-local-media-path / \
          --dtype bfloat16
    ulimits:
      memlock: 67108864
      stack: 67108864
    ipc: host
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ["6"]
              capabilities: [gpu]
    healthcheck:
      test: ["CMD-SHELL", "curl -f http://localhost:30000/health -H 'Authorization: Bearer sk_prod_sXgHYxfVvZdw7O-cki6i7Cp2TbguOvbA_f4beb12a' || exit 1"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 180s
    logging:
      driver: "json-file"
      options:
        max-size: "500m"
        max-file: "3"